Effect of food insecurity on the cognitive problems among elderly in India

Background Food Insecurity (FI) is a crucial social determinant of health, independent of other socioeconomic factors, as inadequate food resources create a threat to physical and mental health especially among older person. The present study explores the associations between FI and cognitive ability among the aged population in India. Methods To measure the cognitive functioning we have used two proxies, word recall and computational problem. Descriptive analysis and multivariable logistic regression was used to understand the prevalence of word recall and computational problem by food security and some selected sociodemographic parameters. All the results were reported at 95% confidence interval. Results We have used the data from the first wave of longitudinal ageing study of India (LASI), with a sample of 31,464 older persons 60 years and above. The study identified that 17 and 5% of the older population in India experiencing computational and word recall problem, respectively. It was found that respondents from food secure households were 14% less likely to have word recall problems [AOR:0.86, 95% CI:0.31–0.98], and 55% likely to have computational problems [AOR:0.45, 95% CI:0.29–0.70]. We also found poor cognitive functioning among those experiencing disability, severe ADL, and IADL. Further, factors such as age, education, marital status, working status, health related factors were the major contributors to the cognitive functioning in older adults. Conclusion This study suggest that food insecurity is associated with a lower level of cognition among the elderly in India, which highlight the need of food policy and interventional strategies to address food insecurity, especially among the individuals belonging to lower wealth quintiles. Furthermore, increasing the coverage of food distribution may also help to decrease the burden of disease for the at most risk population. Also, there is a need for specific programs and policies that improve the availability of nutritious food among elderly.

Empirical Bayes Method for Boltzmann Machines

The framework of the empirical Bayes method allows the estimation of the values of the hyperparameters in the Boltzmann machine by maximizing a specific likelihood function referred to as the empirical Bayes likelihood function. However, the maximization is computationally difficult because the empirical Bayes likelihood function involves intractable integrations of the partition function. The method presented in this chapter avoids this computational problem by using the replica method and the Plefka expansion, which is quite simple and fast because it does not require any iterative procedures and gives reasonable estimates under certain conditions.

Time-based binding as a solution to and a limitation for flexible cognition

Why can't we keep as many items as we want in working memory? It has long been debated whether this resource limitation is a bug (a downside of our fallible biological system) or instead a feature (an optimal response to a computational problem). We propose that the resource limitation is a consequence of a useful feature. Specifically, we propose that flexible cognition requires time-based binding, and time-based binding necessarily limits the number of (bound) memoranda that can be stored simultaneously. Time-based binding is most naturally instantiated via neural oscillations, for which there exists ample experimental evidence. We report simulations that illustrate this theory and that relate it to empirical data. We also compare the theory to several other (feature and bug) resource theories.

Effect of Food Insecurity On The Cognitive Problems Among Elderly In India

Background: Food Insecurity (FI) is a crucial social determinant of health, independent of other socioeconomic factors, as inadequate food resources create a threat to physical and mental health especially among older person. The present study explores the associations between FI and cognitive ability among the aged population in India. Methods: We have used the data from the first wave of longitudinal ageing study of India (LASI), with a sample of 31,464 older persons 60 years and above. To measure the cognitive functioning we have used two proxies, word recall and computational problem. Descriptive analysis and multivariable logistic regression was used to understand the prevalence of word recall and computational problem by food security and some selected sociodemographic parameters. All the results were reported at 95% confidence interval. Results: The study identified that 17% and 5% of the older population in India experiencing computational and word recall problem, respectively. It was found that respondents from food secure households were 14 percent less likely to have word recall problems [AOR:0.86, 95% CI:0.31-0.98], and 55 percent likely to have computational problems [AOR:0.45, 95% CI:0.29-0.70]. We also found poor cognitive functioning among those experiencing disability, severe ADL, and IADL. Further, factors such as age, education, marital status, working status, health related factors were the major contributors to the cognitive functioning in older adults. Conclusion: This study suggest that food insecurity is associated with a lower level of cognition among the elderly in India, which highlight the need of food policy and interventional strategies to address food insecurity, especially among the individuals belonging to lower wealth quintiles. Furthermore, increasing the coverage of food distribution may also help to decrease the burden of disease for the at most risk population. Also, there is a need for specific programs and policies that improve the availability of nutritious food among elderly.

Determining Action Reversibility in STRIPS Using Answer Set and Epistemic Logic Programming

In the context of planning and reasoning about actions and change, we call an action reversible when its effects can be reverted by applying other actions, returning to the original state. Renewed interest in this area has led to several results in the context of the PDDL language, widely used for describing planning tasks. In this paper, we propose several solutions to the computational problem of deciding the reversibility of an action. In particular, we leverage an existing translation from PDDL to Answer Set Programming (ASP), and then use several different encodings to tackle the problem of action reversibility for the STRIPS fragment of PDDL. For these, we use ASP, as well as Epistemic Logic Programming (ELP), an extension of ASP with epistemic operators, and compare and contrast their strengths and weaknesses.

Security estimates of the NTRUCipher and NTRUCipher+ encryption schemes against BKW-attack

Due to the need of creation a symmetric encryption scheme for practical usage, the security of which (similarly to asymmetric cryptosystems) is based on the difficulty of solving only one computational problem, in 2017 the NTRUCipher encryption scheme was proposed. Preliminary researches of this encryption scheme have been conducted, but the question of NTRUCipher’s security to certain specific attacks is open. This article provides estimates of the complexity of chosen-plaintext attack on the NTRUCipher encryption scheme and even on its natural improvement NTRUCipher+. The given analytical estimates allow to compare the security of these encryption schemes and to make a conclusion about inexpediency of usage the NTRUCipher+ encryption scheme for its increase.

Toward a 5E-Based Flipped Classroom Model for Teaching Computational Thinking in Elementary School: Effects on Student Computational Thinking and Problem-Solving Performance

Computational thinking (CT) has attracted significant interest among many educators around the globe. Despite this growing interest, research on CT and programming education in elementary school remains at an initial stage. Many relevant studies have adopted only one type of method to assess students’ CT, which may lead to an incomplete view of student development on CT, while other studies employed small sample sizes, which may increase the chance of assuming a false premise to be true. Moreover, conventional programming courses typically have two limitations (e.g., limited student active learning and student low engagement). Given these gaps, this study investigates the effects of a theory-based (5E framework) flipped classroom model (FCM) on elementary school students’ understanding of CT concepts, computational problem-solving performance, and perceptions of flipped learning. To achieve this, a pretest-posttest quasi-experimental study was conducted in a rural elementary school, including 125 students in the experimental group and 122 students in the control group. The results showed that the 5E-based FCM significantly improved student understanding of CT concepts and computational problem-solving abilities. The results also revealed positive student perception toward the FCM. The benefits and challenges of the 5E-based FCM are discussed.

DATA-DRIVEN CREATIVITY: COMPUTATIONAL PROBLEM-EXPLORING IN ENGINEERING DESIGN

Creativity is required in engineering design. It is required in the aspects of problem-solving - conceptualizing a new solution to a problem, and problem-exploring - conceptualizing a new problem. Studies show that, in both aspects, creativity is a difficult task in practice. The aim of this study is to support the engineering design community by easing the difficulty in the problem-exploring practice. To achieve this, a computational problem-exploring (CPE) model is developed to mimic how design engineers identify a valid design problem. Consequently, a CPE tool - Pro-Explora V1 is developed based on the CPE model. The CPE model consists of a synergy of emergent computational technologies including data retrieval and machine learning. A Markovian model is employed in the CPE model to enable a data-driven random process for exploring design problems. In pilot test, Pro-Explora V1 generated some engineering design-related problems which are meaningful, unique, and could not be distinguished from naturally generated ones. It provides support to design engineers in problem-exploring at the early stage in engineering design. This study contributes to the global effort towards data-driven processes in the fourth industrial revolution.

On the Hybrid Power Mean Involving the Character Sums and Dedekind Sums

The main purpose of this paper is to use the elementary and analytic methods, the properties of Gauss sums, and character sums to study the computational problem of a certain hybrid power mean involving the Dedekind sums and a character sum analogous to Kloosterman sum and give two interesting identities for them.

A computational problem involving Dickson conjecture

In this paper, we give an equivalent form of Dickson’s conjecture. Based on this equivalent form, we propose a computational problem and obtain several interesting results.